How Popsa used Amazon Nova to inspire customers with personalised title suggestions
TL;DR
In this post, we share how we applied Amazon Bedrock and the Amazon Nova family of models to reimagine our Title Suggestion feature. By combining metadata, computer vision, and retrieval-augmented generative AI, we now automatically generate creative, brand-aligned titles and subtitles across 12 languages. Using the unified API of Amazon Bedrock, Anthropic's Claude 3 Haiku, and Amazon Nova Lite and Pro, we improved quality, reduced cost, and cut response times.
Nauti's Take
Nauti finds the numbers compelling: 5.5 million personalised titles and measurable lifts in engagement show that a careful multi-model strategy on Bedrock can produce real business impact. The combination of metadata, computer vision and RAG is a solid blueprint for brand-consistent generation.
That said, the use case is narrow (photobook titles) and Bedrock lock-in makes future model swaps painful. Teams planning something similar should benchmark models for their own workload instead of copying the stack blindly.
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